Abstract:

To clarify the predictive capability of the fifth-generation seasonal forecast system (SEAS5) of the European Centre for Medium-Range Weather Forecasts for summer precipitation in Heilongjiang and to provide a basis for improving regional seasonal prediction and its interpretative application, this study employs SEAS5 historical reforecast and real-time forecast data during 1993-2023 together with precipitation observations from 83 meteorological stations in Heilongjiang Province, and uses verification methods, including the anomaly correlation coefficient (ACC) and Ps score, to systematically evaluate the model performance and its underlying causes. The results show that: (1) In terms of total precipitation, SEAS5 generally reproduces the spatial distribution consistent with observations, but the high-value center is shifted southward, interannual variability is underestimated, and a wet bias prevails over most of the province. The forecasts initialized in March exhibit higher skill than those initialized in April and May. For precipitation anomalies, the multi-year mean ACC for different initialization months shows negative skill, and only a few years have a Ps score exceeding 80 points, with March initialization showing relatively better performance. (2) The model’s ability to represent the circulation associated with the northeast cold vortex (NCV) is a key factor affecting the prediction skill of summer precipitation in Heilongjiang. In high-skill years, the model can reasonably reproduce NCV-induced circulation and corresponding precipitation anomalies, whereas in low-skill years significant biases occur in the prediction of low-level circulation over northeast China and adjacent regions. (3) The March initialization performs relatively better due to a more reasonable prediction of the spatial distribution of upper-tropospheric circulation. However, errors in the middle- and lower-tropospheric circulation still limit further improvement of skill. In addition, the predictive capability of the western Pacific subtropical high shows weak correlation with the summer precipitation skill in Heilongjiang, while the influence of NCV-related circulation is more direct and critical.

Key words: Heilongjiang summer precipitation, SEAS5, model evaluation, low-level circulation, northeast cold vortex

摘要：

为明确欧洲中期天气预报中心第五代季节预测系统（the Fifth Generation Seasonal Forecast System，SEAS5）季节模式对黑龙江汛期降水的预测能力，并为提升区域季节预测与解释应用水平提供依据，基于SEAS5模式1993—2023年的历史回报与实时预报数据及黑龙江省83个气象站降水观测资料，利用距平相关系数、Ps评分等检验评估方法，对该模式的夏季降水预测性能进行系统评估。结果表明：（1）SEAS5模式对黑龙江夏季降水总量空间分布的刻画与观测较为一致，但高值中心偏南、年际变率偏小、全省以湿偏差为主，3月起报的预测技巧优于4月和5月起报。就降水距平而言，不同月份起报的多年平均距平相关系数均为负技巧，仅有个别年份Ps评分超过80分，3月起报的预测相对表现更优。（2）模式对东北冷涡相关环流的刻画能力是影响黑龙江夏季降水预测技巧的关键因素。高技巧年份能较好再现冷涡引起的环流异常及其对应的降水异常，而低技巧年份在东北及其邻近区域的低层环流预测偏差显著。（3）3月起报因对对流层高层环流空间分布的预测更为合理而表现相对较优，但中低层环流误差仍制约整体技巧提升；SEAS5对西太平洋副热带高压的预测能力与黑龙江夏季降水技巧关联较弱，东北冷涡相关环流的影响更为直接。

关键词: 黑龙江夏季降水, SEAS5, 模式评估, 低层环流, 东北冷涡